Sybase is another Relational Database Management System (RDBMS), it has long well established history.  Today Sybase is part of SAP (Since November 2012). But in earlier days Sybase and Microsoft has worked together.

In 1986 Microsoft and Sybase worked together to build a product called Ashton-Tate/SQL Server 1.0. Later in 1993 they dissolved partnership and Microsoft got the code base of SQL Server side of the product and continued their investments into it to have it more adaptable for Windows.

As Sybase and SQL Server has same roots and the core code base which is closely tied with each other then it’s safe to assume that their syntax is very close to each other if it is not 100% same to same.

Besides, I have worked on Oracle in quite detailed level and then I completely focused on Microsoft Technologies. While working with SQL Sever I learned that all databases are derived from some standards like ANSI SQL. Hence, syntax of any two database won’t be much different and besides all of those have support for same database constructs like JOINS, SETS, Query Operators etc. including db objects like Tables, Indexes, Views, Triggers, Stored Procedures etc.

However, I can say that some database may showcase different syntax over another, for example I recall that in Oracle 7.3 for Left Outer Join the operator was “*= ” whereas in SQL Server you can say “LEFT OUTER JOIN”.

So, if someone is really focused on Syntax part and hard core fundamentals concept then it is very easy to reduce the learning curve of any new technology.

Introduction to Big Data

June 12th, 2014 | Posted by Vidya Vrat in Database - (0 Comments)

Data is a precious thing because they last longer than systems – Tim Barnes Lee


Big Data, as the name implies, is a collection of huge amounts of data. Data has always been important to mankind and society by various means. But in the past few years data has been collected and used for a variety of purposes. The major factor that differs Big Data from normal data in a DBMS or RDBMS is that Big Data is very large volume, it has no defined structure, it includes a lot of data that is being created from various channels like emails or social media like Twitter, Facebook, LinkedIn and so on.

Read My Full Article Here

As a .NET Developer most of the common tasks you do are database related operations, like INSERT, SELECT UPDATE and DELETE. These tasks are often collectively referred to as CRUD operations. The problem comes when writing a complex query directly or in a Stored Procedure that retrieves expected data from more than one table of your Normalized database, in other words you are working on “Joining the Tables” to pull the data. Read Full Article Here


  • Creating two sample tables for Join
  • Insert data into sample Join tables
  • Inner Join
  • Left Outer Join
  • Right Outer Join
  • Full Outer Join
  • Cross Join

Understanding Transactions

September 29th, 2013 | Posted by Vidya Vrat in Database | SQL Server - (0 Comments)

For any business, transactions that may be comprised of many individual operations and even other transactions, play a key role. Transactions are essential for maintaining data integrity, both for multiple related operations and when multiple users that update the database concurrently.

This article will specifically talk about the concepts related to transactions and how transactions can be used in the context of a SQL Server database. Besides, a transaction is a fundamental concept and this article will be helpful for relating transaction concepts with other databases as well.

Read Full Article Here

Introduction to Big Data

June 5th, 2013 | Posted by Vidya Vrat in Database - (0 Comments)

Big Data

Data is a precious thing because they last longer than systems – Tim Barnes Lee


Big Data, as the name describes itself, it is collection of huge amount of data. Data has always been important to mankind and society by various means.  But during past few years data is collected and used for variety of purposes.  The major factor which differs Big Data from normal Data which can be handled in a DBMS or RDBMS is that; Big Data is very large volume, it has no defined structure, it includes whole lot of data which is being created from various channels like emails or social media like twitter, Facebook, LinkedIn etc.

What can be done with a lot of data?

When we have a gathered data, the best use data can be made by following three ways:

1-  To know what has happened

2- To understand and explain why it actually happened

3- Most importantly predict what will happen

Big Data was always around but this term became more popular in the recent time.  Think of a weather forecast system which can predict weather based on data collected. Another great example is traffic support system of a GPS, which is reading data from various satellites to re-direct you to the roads with less traffic or highways etc. If you dig into the details how these systems are being made and trusted is fully based on their capabilities of acquiring, collecting, processing and then doing a predictive analysis with that data to produce results which are almost accurate.

Until past few years forecasting and predictive analysis with data was done by National Weather Labs, Intelligence community etc. but now it is much more since then.

How Big Data is being captured and who contributes to Big Data

Big Data has grown tremendously and it’s increasing like anything in an uncontrollable fashion. Most of the world’s data today approx 90% was generated in last two years. The reason of that is our day to day contribution in various digital forms of data for example, Facebook, tweets, Pictures etc.
Hence, it won’t be surprising that in fact web does millions of activities per second and so huge chunk of data is being stored in server logs.  You must have heard that goggle stores and some people say steals all the information of your activities. For example, your search strings. This is same with any search engine.

One of the most interesting question is that who actually contributes to thi huge data building process. Well the answer is simple, WE. Yes, we all are helping the various companies to gather, process and then predict via the data which is being contributed on day to day basis by approx over 800 million active Facebook users, approx over  40 billion photos, over 200 million active users on Twitter etc. Just FYI  Facebook’s Big data analytics tool can process more than 20 billion events a day.

So, whatever you do actually adds into the avalanche of data for further processing to serve the mankind with the information they need and most importantly at the right time when they would really need it (an example will follow in the article below).

Two Great Examples where Big Data changed the world


You must not have forgotten Amir Khan’s Stayamev Jayate, one of the most popular show released in May 2012, was using Big Data. During the execution of the show 1000+ engineers were working behind the scene to capture all the data that will be created on Facebook, twitter, websites and blogs etc. to actually capture not only the opinion about the show, but category of people, from where including count of positive and negatives etc.

The producers utilized the technology to define the future episodes, the channel reported traffic of 40,000+ tweets during the 90 minutes of the show.


Obama the President of USA, he was depending on Big Data for his election campaign. His app “Obama for America” connected all the people who were in favor of him and join the campaign. 2+ million joined on this app, and this app will show you people in your neighborhood who likes Obama, their name, age, address and gender etc. including various other personal details.


How Big Data is being used today and what is next

Based on your search in Bing and google, you will observe some advertisements on your social media sites like Facebook which are related to your searches. Companies are working on interesting path which not only utilizes Big Data but also combine various technologies together. Assume, in near future you walked into a store and based on your last purchases made in the store you start getting information about the deals, discounts etc. on your phone, twitter etc.

To make this possible, store needs to grab all the data including your purchases, your Facebook likes, your searches on various search engines etc. and as soon as you enter into the store they sense you buy your handheld device and start analyzing and processing the data to predict what you might like based on the patterns of your purchase and search history interesting isn’t it?